Euclidean Skeletons of 3D Data Sets in Linear Time by the Integer Medial Axis Transform

Abstract

A general algorithm for computing Euclidean skeletons of 3D data sets in linear time is presented. These skeletons are defined in terms of a new concept, called the integer medial axis (IMA) transform. The algorithm is based upon the computation of 3D feature transforms, using a modification of an algorithm for Euclidean distance transforms. The skeletonization algorithm has a time complexity which is linear in the amount of voxels, and can be easily parallelized. The relation of the IMA skeleton to the usual definition in terms of centers of maximal disks is discussed.